Analysis of the calving pattern of herds in small-scale dairy systems in central Mexico

This study sets out to find the best calving pattern for small-scale dairy systems in Michoacan State, central Mexico. Two models were built. First, a linear programming model was constructed to optimize calving pattern and herd structure according to metabolizable energy availability. Second, a Markov chain model was built to investigate three reproductive scenarios (good, average and poor) in order to suggest factors that maintain the calving pattern given by the linear programming model. Though it was not possible to maintain the optimal linear programming pattern, the Markov chain model suggested adopting different reproduction strategies according to period of the year that the cow is expected to calve. Comparing different scenarios, the Markov model indicated the effect of calving interval on calving pattern and herd structure.

Analysis of chain and blood group type and branching pattern of sialylated oligosaccharides by negative ion electrospray tandem mass spectrometry

We previously reported sequence determination of neutral oligosaccharides by negative ion electrospray tandem mass spectrometry on a quadrupole-orthogonal time-of-flight instrument with high sensitivity and without the need of derivatization. In the present report, we extend our strategies to sialylated oligosaccharides for analysis of chain and blood group types together with branching patterns. A main feature in the negative ion mass spectrometry approach is the unique double glycosidic cleavage induced by 3-glycosidic substitution, producing characteristic D-type fragments which can be used to distinguish the type 1 and type 2 chains, the blood group related Lewis determinants, 3,6-disubstituted core branching patterns, and to assign the structural details of each of the branches. Twenty mono- and disialylated linear and branched oligosaccharides were used for the investigation, and the sensitivity achieved is in the femtomole range. To demonstrate the efficacy of the strategy, we have determined a novel complex disialylated and monofucosylated tridecasaccharide that is based on the lacto-N-decaose core. The structure and sequence assignment was corroborated by :methylation analysis and H-1 NMR spectroscopy.

Analysis of the regional pattern of sea level change due to ocean dynamics and density changes for 1993-2099 in observations and CMIP5 AOGCMs

Predictions of twenty-first century sea level change show strong regional variation. Regional sea level change observed by satellite altimetry since 1993 is also not spatially homogenous. By comparison with historical and pre-industrial control simulations using the atmosphere–ocean general circulation models (AOGCMs) of the CMIP5 project, we conclude that the observed pattern is generally dominated by unforced (internal generated) variability, although some regions, especially in the Southern Ocean, may already show an externally forced response. Simulated unforced variability cannot explain the observed trends in the tropical Pacific, but we suggest that this is due to inadequate simulation of variability by CMIP5 AOGCMs, rather than evidence of anthropogenic change. We apply the method of pattern scaling to projections of sea level change and show that it gives accurate estimates of future local sea level change in response to anthropogenic forcing as simulated by the AOGCMs under RCP scenarios, implying that the pattern will remain stable in future decades. We note, however, that use of a single integration to evaluate the performance of the pattern-scaling method tends to exaggerate its accuracy. We find that ocean volume mean temperature is generally a better predictor than global mean surface temperature of the magnitude of sea level change, and that the pattern is very similar under the different RCPs for a given model. We determine that the forced signal will be detectable above the noise of unforced internal variability within the next decade globally and may already be detectable in the tropical Atlantic.

Analysis of dietary pattern impact on weight status for personalised nutrition through on-line advice: the Food4Me Spanish cohort

Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r2 = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r2 = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Analysis of EnterpriseVoIP Traffic from aWire line IMS System

With the rapid development of telecommunication industry, the IP multimedia Subsystem (IMS) could very well be the panacea for most telecom operators. It is originally defined as the core network for 3G mobile systems by the 3rd Generation Partnership Project (3GPP), the more recent development is merging between fixed line network and wireless networkd This report researchs the characteristic of the IMS data and proposes an IMS characterization analysis. We captured the IMS traffic data with 10 tousands users for about 41 hours. By analyzing the characteristics of the IMS, we know that the most important application in the IMS is VoIP call. Then we use the tool designed by Tsinghua University & Ericsson Company to recognize the data, and the results we got can be used to build the traffic models. From the results of the traffic models, I will get some reasons and conclusion. The traffic model gives out the types of session and types of VoIP call. I bring into a concept—busy hour. This concept is very important because it can help us to know which period is the peak of the VoIP call. The busy hour is from 10:00 to 11:00 in the morning. I also bring into another concept—connection ratio. This concept is significant because it can evaluate whether the VoIP call is good when it use IMS network. By comparing the traffic model with other one’s models, we found the different results from them, both the accuracy and the busy hour. From the contract, we got the advantages of our traffic models.

Analysis of mechanical behavior of implant-supported prostheses in the anterior maxilla: analysis by speckle pattern interferometry

The use of implants to rehabilitation of total edentulous, partial edentulous or single tooth is increasing, it is due to the high rate of success that this type of treatment present. The objective of this study was to analyze the mechanical behavior of different positions of two dental implants in a rehabilitation of 4 teeth in the region of maxilla anterior. The groups studied were divided according the positioning of the implants. The Group 1: Internal Hexagonal implant in position of lateral incisors and pontic in region of central incisors; Group 2: Internal Hexagonal implant in position of central incisors and cantilever of the lateral incisors and Group3 - : Internal Hexagonal implants alternate with suspended elements. The Electronic Speckle Pattern Interferometry (ESPI) technique was selected for the mechanical evaluation of the 3 groups performance. The results are shown in interferometric phase maps representing the displacement field of the prosthetic structure.

In Vitro Study of Fracture Load and Fracture Pattern of Ceramic Crowns: A Finite Element and Fractography Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

GC Fingerprints Coupled to Pattern-Recognition Multivariate SIMCA Chemometric Analysis for Brazilian Gasoline Quality Studies

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Screening Brazilian commercial gasoline quality by hydrogen nuclear magnetic resonance spectroscopic fingerprintings and pattern-recognition multivariate chemometric analysis

The identification of gasoline adulteration by organic solvents is not an easy task, because compounds that constitute the solvents are already in gasoline composition. In this work, the combination of Hydrogen Nuclear Magnetic Resonance ((1)H NMR) spectroscopic fingerprintings with pattern-recognition multivariate Soft Independent Modeling of Class Analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a Monitoring Program for Quality Control of Automotive Fuels. SIMCA was performed on spectroscopic fingerprints to classify the quality of representative commercial gasoline samples selected by Hierarchical Cluster Analysis (HCA) and collected over a 6-month period from different gas stations in the São Paulo state, Brazil. Following optimized the (1)H NMR-SIMCA algorithm, it was possible to correctly classify 92.0% of commercial gasoline samples, which is considered acceptable. The chemometric method is recommended for routine applications in Quality-Control Monitoring Programs, since its measurements are fast and can be easily automated. Also, police laboratories could employ this method for rapid screening analysis to discourage adulteration practices. (C) 2010 Elsevier B.V. All rights reserved.

Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative analysis of electromyographic pattern in the forearm muscles of hemiplegic patients

It was purposed the use of electromyography (EMG) to evaluate the activation of the agonists and antagonists muscles of spastic patients, to test the viability in the development of an instrument that given quantitative data of the patient spasticity. 30 hemiplegic and 15 normal volunteers had been submitted to the EMG of flexor and extensor carpi ulnaris muscles during the flexion and extension movements of the wrist. The individuals with less severe spasticity (mAS (modified Ashworth Scale) ringing 0 to 3 degree), had presented deficit in the activation of the flexor muscles in plegic side in relation to the non plegic side and that the individuals seriously compromised by the spasticity (mAS = 4 degree) present deficit of reciprocal inhibition. One evidenced is that the non plegic member does not present a similar neuro-motor comportment when compared to the normal member. The surface electromyography is a practical clinical instrument to evaluate the patient with spasticity and the hemiplegic patient needs to be evaluated on both sides (deficient and no deficient) because the no compromised side do not show a normality standard.